{"id":"W2591555204","doi":"10.1111/1365-2435.12847","title":"Using a forest dynamics model to link community assembly processes and traits structure","year":2017,"lang":"en","type":"article","venue":"Functional Ecology","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministère de l'Education Nationale, de l'Enseignement Superieur et de la Recherche; Agence Nationale de la Recherche; McGill University","keywords":"Trait; Ecology; Competition (biology); Niche; Forest dynamics; Community structure; Convergence (economics); Environmental gradient; Species richness; Biology; Productivity; Divergence (linguistics); Environmental change; Tree (set theory); Climate change; Computer science; Economics; Mathematics; Habitat","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0001310361,0.00009799383,0.0001266218,0.00002632857,0.001759771,0.0000288133,0.0001671765,0.0001181506,0.00008915347],"category_scores_gemma":[0.0003372691,0.00009380626,0.00001517413,0.00004053747,0.0002847733,0.0001779806,0.0003418129,0.0002126752,0.00002190415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000123299,"about_ca_system_score_gemma":0.00003857956,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001033649,"about_ca_topic_score_gemma":0.1023074,"domain_scores_codex":[0.9994342,0.00004102648,0.0001108619,0.0001680424,0.00007057758,0.0001752766],"domain_scores_gemma":[0.9995426,0.0001342352,0.00009062429,0.0001407917,0.00003211444,0.00005965367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003779756,0.00004441349,0.6250629,0.00002176771,0.00002692145,0.000001620077,0.000351749,0.3704017,0.0002049356,0.003213928,0.0001851358,0.0004472176],"study_design_scores_gemma":[0.0001496209,0.00005954583,0.7096466,0.000002389191,0.00001250365,0.00001435215,0.00005648534,0.2730865,0.000003551288,0.01686589,0.00002757082,0.00007504592],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831542,0.000004842641,0.0127133,0.001388309,0.0001675985,0.000126534,0.00003256504,0.00001602238,0.002396637],"genre_scores_gemma":[0.9949308,0.000003297989,0.003904189,0.0006675828,0.00003431315,0.00001440792,0.00001536681,0.000007191154,0.0004228248],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.102204,"threshold_uncertainty_score":0.9995398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04390270830289916,"score_gpt":0.2811081698375267,"score_spread":0.2372054615346276,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}